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Enter the query into the form above. You can look for specific version of a package by using @ symbol like this: gcc@10.

API method:

GET /api/packages?search=hello&page=1&limit=20

where search is your query, page is a page number and limit is a number of items on a single page. Pagination information (such as a number of pages and etc) is returned in response headers.

If you'd like to join our channel webring send a patch to ~whereiseveryone/toys@lists.sr.ht adding your channel as an entry in channels.scm.


r-polarcap 1.0.1
Propagated dependencies: r-tidyr@1.3.1 r-countrycode@1.6.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/imehlhaff/PolarCAP
Licenses: CC0
Build system: r
Synopsis: Access the Polarization in Comparative Attitudes Project
Description:

Distributes data from the Polarization in Comparative Attitudes Project. Helper functions enable data retrieval in wide and tidy formats for user-defined countries and years. Provides support for case-insensitive country names in many languages. Mehlhaff (2022) <https://imehlhaff.net/files/Polarization%20and%20Democracy.pdf>.

r-pliman 3.1.1
Propagated dependencies: r-terra@1.8-86 r-sf@1.0-23 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-purrr@1.2.0 r-mirai@2.5.2 r-exactextractr@0.10.0 r-dplyr@1.1.4 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://nepem-ufsc.github.io/pliman/
Licenses: GPL 3+
Build system: r
Synopsis: Tools for Plant Image Analysis
Description:

This package provides tools for both single and batch image manipulation and analysis (Olivoto, 2022 <doi:10.1111/2041-210X.13803>) and phytopathometry (Olivoto et al., 2022 <doi:10.1007/S40858-021-00487-5>). The tools can be used for the quantification of leaf area, object counting, extraction of image indexes, shape measurement, object landmark identification, and Elliptical Fourier Analysis of object outlines (Claude (2008) <doi:10.1007/978-0-387-77789-4>). The package also provides a comprehensive pipeline for generating shapefiles with complex layouts and supports high-throughput phenotyping of RGB, multispectral, and hyperspectral orthomosaics. This functionality facilitates field phenotyping using UAV- or satellite-based imagery.

r-ptak 2.0.0
Propagated dependencies: r-tensor@1.5.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://www.GeotRYcs.com
Licenses: GPL 2+
Build system: r
Synopsis: Principal Tensor Analysis on k Modes
Description:

This package provides a multiway method to decompose a tensor (array) of any order, as a generalisation of SVD also supporting non-identity metrics and penalisations. 2-way SVD with these extensions is also available. The package includes also some other multiway methods: PCAn (Tucker-n) and PARAFAC/CANDECOMP with these extensions.

r-piecemaker 1.0.2
Propagated dependencies: r-stringr@1.6.0 r-stringi@1.8.7 r-rlang@1.1.6 r-glue@1.8.0 r-cli@3.6.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/macmillancontentscience/piecemaker
Licenses: FSDG-compatible
Build system: r
Synopsis: Tools for Preparing Text for Tokenizers
Description:

Tokenizers break text into pieces that are more usable by machine learning models. Many tokenizers share some preparation steps. This package provides those shared steps, along with a simple tokenizer.

r-pcse 1.9.1.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=pcse
Licenses: GPL 3+
Build system: r
Synopsis: Panel-Corrected Standard Error Estimation in R
Description:

This package provides a function to estimate panel-corrected standard errors. Data may contain balanced or unbalanced panels.

r-pcgse 0.5.0
Propagated dependencies: r-rmtstat@0.3.1 r-mass@7.3-65
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PCGSE
Licenses: GPL 2+
Build system: r
Synopsis: Principal Component Gene Set Enrichment
Description:

This package contains logic for computing the statistical association of variable groups, i.e., gene sets, with respect to the principal components of genomic data.

r-polypatex 0.9.2
Propagated dependencies: r-gtools@3.9.5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PolyPatEx
Licenses: FSDG-compatible
Build system: r
Synopsis: Paternity Exclusion in Autopolyploid Species
Description:

This package provides functions to perform paternity exclusion via allele matching, in autopolyploid species having ploidy 4, 6, or 8. The marker data used can be genotype data (copy numbers known) or allelic phenotype data (copy numbers not known).

r-pboost 0.2.1
Propagated dependencies: r-survival@3.8-3 r-quantreg@6.1 r-matrix@1.7-4 r-mass@7.3-65 r-formula@1.2-5 r-betareg@3.2-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/paradoxical-rhapsody/pboost
Licenses: GPL 3+
Build system: r
Synopsis: Profile Boosting Framework for Parametric Models
Description:

This package provides a profile boosting framework for feature selection in parametric models. It offers a unified interface pboost() and several wrapped models, including linear model, generalized linear models, quantile regression, Cox proportional hazards model, beta regression. An S3 interface EBIC() is provided as the stopping rule for the profile boosting by default.

r-panelview 1.1.18
Propagated dependencies: r-gridextra@2.3 r-ggplot2@4.0.1 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://yiqingxu.org/packages/panelview/index.html
Licenses: Expat
Build system: r
Synopsis: Visualizing Panel Data
Description:

Visualizes panel data. It has three main functionalities: (1) it plots the treatment status and missing values in a panel dataset; (2) it visualizes the temporal dynamics of a main variable of interest; (3) it depicts the bivariate relationships between a treatment variable and an outcome variable either by unit or in aggregate. For details, see <doi:10.18637/jss.v107.i07>.

r-phyloraster 2.3.0
Propagated dependencies: r-terra@1.8-86 r-sesraster@0.7.1 r-purrr@1.2.0 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://CRAN.R-project.org/package=phyloraster
Licenses: GPL 3+
Build system: r
Synopsis: Evolutionary Diversity Metrics for Raster Data
Description:

Phylogenetic Diversity (PD, Faith 1992), Evolutionary Distinctiveness (ED, Isaac et al. 2007), Phylogenetic Endemism (PE, Rosauer et al. 2009; Laffan et al. 2016), and Weighted Endemism (WE, Laffan et al. 2016) for presence-absence raster. Faith, D. P. (1992) <doi:10.1016/0006-3207(92)91201-3> Isaac, N. J. et al. (2007) <doi:10.1371/journal.pone.0000296> Laffan, S. W. et al. (2016) <doi:10.1111/2041-210X.12513> Rosauer, D. et al. (2009) <doi:10.1111/j.1365-294X.2009.04311.x>.

r-psricalcsm 1.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/RFeissIV/PSRICalcSM
Licenses: Expat
Build system: r
Synopsis: Plant Stress Response Index Calculator - Softmax Method
Description:

This package implements the softmax aggregation method for calculating Plant Stress Response Index (PSRI) from time-series germination data under environmental stressors including prions, xenobiotics, osmotic stress, heavy metals, and chemical contaminants. Provides zero-robust PSRI computation through adaptive softmax weighting of germination components (Maximum Stress-adjusted Germination, Maximum Rate of Germination, complementary Mean Time to Germination, and Radicle Vigor Score), eliminating the zero-collapse failure mode of the geometric mean approach implemented in PSRICalc'. Includes perplexity-based temperature parameter calibration and modular component functions for transparent germination analysis. Built on the methodological foundation of the Osmotic Stress Response Index (OSRI) framework developed by Walne et al. (2020) <doi:10.1002/agg2.20087>. Note: This package implements methodology currently under peer review. Please contact the author before publication using this approach. Development followed an iterative human-machine collaboration where all algorithmic design, statistical methodologies, and biological validation logic were conceptualized, tested, and iteratively refined by Richard A. Feiss through repeated cycles of running experimental data, evaluating analytical outputs, and selecting among candidate algorithms and approaches. AI systems (Anthropic Claude and OpenAI GPT) served as coding assistants and analytical sounding boards under continuous human direction. The selection of statistical methods, evaluation of biological plausibility, and all final methodology decisions were made by the human author. AI systems did not independently originate algorithms, statistical approaches, or scientific methodologies.

r-pool 1.0.4
Propagated dependencies: r-rlang@1.1.6 r-r6@2.6.1 r-later@1.4.4 r-dbi@1.2.3
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/rstudio/pool
Licenses: Expat
Build system: r
Synopsis: Object Pooling
Description:

Enables the creation of object pools, which make it less computationally expensive to fetch a new object. Currently the only supported pooled objects are DBI connections.

r-predtest 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PredTest
Licenses: Expat
Build system: r
Synopsis: Preparing Data For, and Calculating the Prediction Test
Description:

Global hypothesis tests combine information across multiple endpoints to test a single hypothesis. The prediction test is a recently proposed global hypothesis test with good performance for small sample sizes and many endpoints of interest. The test is also flexible in the types and combinations of expected results across the individual endpoints. This package provides functions for data processing and calculation of the prediction test.

r-phyr 1.1.3
Propagated dependencies: r-tidyr@1.3.1 r-rcpparmadillo@15.2.2-1 r-rcpp@1.1.0 r-nloptr@2.2.1 r-mvtnorm@1.3-3 r-matrix@1.7-4 r-lme4@1.1-37 r-latticeextra@0.6-31 r-gridextra@2.3 r-dplyr@1.1.4 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://daijiang.github.io/phyr/
Licenses: GPL 3
Build system: r
Synopsis: Model Based Phylogenetic Analysis
Description:

This package provides a collection of functions to do model-based phylogenetic analysis. It includes functions to calculate community phylogenetic diversity, to estimate correlations among functional traits while accounting for phylogenetic relationships, and to fit phylogenetic generalized linear mixed models. The Bayesian phylogenetic generalized linear mixed models are fitted with the INLA package (<https://www.r-inla.org>).

r-pottsutils 0.3-3.1
Propagated dependencies: r-miscf@0.1-5
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PottsUtils
Licenses: GPL 2
Build system: r
Synopsis: Utility Functions of the Potts Models
Description:

There are three sets of functions. The first produces basic properties of a graph and generates samples from multinomial distributions to facilitate the simulation functions (they maybe used for other purposes as well). The second provides various simulation functions for a Potts model in Potts, R. B. (1952) <doi:10.1017/S0305004100027419>. The third currently includes only one function which computes the normalizing constant of a Potts model based on simulation results.

r-prior3d 0.1.5
Propagated dependencies: r-viridis@0.6.5 r-terra@1.8-86 r-readxl@1.4.5 r-rasterdiv@0.3.8 r-prioritizr@8.1.0 r-maps@3.4.3 r-highs@1.12.0-1 r-geodiv@1.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/cadam00/prior3D
Licenses: GPL 3
Build system: r
Synopsis: 3D Prioritization Algorithm
Description:

Three-dimensional systematic conservation planning, conducting nested prioritization analyses across multiple depth levels and ensuring efficient resource allocation throughout the water column. It provides a structured workflow designed to address biodiversity conservation and management challenges in the 3 dimensions, while facilitating usersâ choices and parameterization (Doxa et al. 2025 <doi:10.1016/j.ecolmodel.2024.110919>).

r-plottools 0.4.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://ms609.github.io/PlotTools/
Licenses: GPL 2+
Build system: r
Synopsis: Extended Tools for Continuous Legends, Polygon Manipulation, and Visual Display of Categorical Data
Description:

Annotate plots with legends for continuous variables and colour spectra using the base graphics plotting tools; and manipulate irregular polygons. Includes palettes for colour-blind viewers.

r-pairwisellm 1.1.0
Propagated dependencies: r-tidyselect@1.2.1 r-tibble@3.3.0 r-rlang@1.1.6 r-jsonlite@2.0.0 r-httr2@1.2.1 r-dplyr@1.1.4 r-curl@7.0.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/shmercer/pairwiseLLM
Licenses: Expat
Build system: r
Synopsis: Pairwise Comparison Tools for Large Language Model-Based Writing Evaluation
Description:

This package provides a unified framework for generating, submitting, and analyzing pairwise comparisons of writing quality using large language models (LLMs). The package supports live and/or batch evaluation workflows across multiple providers ('OpenAI', Anthropic', Google Gemini', Together AI', and locally-hosted Ollama models), includes bias-tested prompt templates and a flexible template registry, and offers tools for constructing forward and reversed comparison sets to analyze consistency and positional bias. Results can be modeled using Bradleyâ Terry (1952) <doi:10.2307/2334029> or Elo rating methods to derive writing quality scores. For information on the method of pairwise comparisons, see Thurstone (1927) <doi:10.1037/h0070288> and Heldsinger & Humphry (2010) <doi:10.1007/BF03216919>. For information on Elo ratings, see Clark et al. (2018) <doi:10.1371/journal.pone.0190393>.

r-padr 0.6.3
Propagated dependencies: r-rlang@1.1.6 r-rcpp@1.1.0 r-lubridate@1.9.4 r-dplyr@1.1.4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://edwinth.github.io/padr/
Licenses: Expat
Build system: r
Synopsis: Quickly Get Datetime Data Ready for Analysis
Description:

Transforms datetime data into a format ready for analysis. It offers two core functionalities; aggregating data to a higher level interval (thicken) and imputing records where observations were absent (pad).

r-primal 1.0.3
Propagated dependencies: r-rcppeigen@0.3.4.0.2 r-rcpp@1.1.0 r-matrix@1.7-4
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PRIMAL
Licenses: GPL 2+
Build system: r
Synopsis: Parametric Simplex Method for Sparse Learning
Description:

This package implements a unified framework of parametric simplex method for a variety of sparse learning problems (e.g., Dantzig selector (for linear regression), sparse quantile regression, sparse support vector machines, and compressive sensing) combined with efficient hyper-parameter selection strategies. The core algorithm is implemented in C++ with Eigen3 support for portable high performance linear algebra. For more details about parametric simplex method, see Haotian Pang (2017) <https://papers.nips.cc/paper/6623-parametric-simplex-method-for-sparse-learning.pdf>.

r-pdindex 0.1.0
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=PDIndex
Licenses: GPL 3
Build system: r
Synopsis: Disease Intensity and Progress Curve Indices for Plant Pathology
Description:

This package provides standardised functions for quantifying plant disease intensity and disease development over time. The package implements Percent Disease Index (PDI) for assessing overall disease severity based on categorical ratings, Area Under the Disease Progress Curve (AUDPC) for summarizing disease progression using trapezoidal integration, and Relative AUDPC (rAUDPC) for expressing disease development relative to the maximum possible severity over the observation period. These indices are widely used in plant pathology and epidemiology for comparing treatments, cultivars, and environments.

r-phylosignaldb 0.4.2
Propagated dependencies: r-foreach@1.5.2 r-doparallel@1.0.17 r-cluster@2.1.8.1 r-castor@1.8.4 r-ape@5.8-1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/anonymous-eco/phylosignalDB
Licenses: GPL 3+
Build system: r
Synopsis: Explore Phylogenetic Signals Using Distance-Based Methods
Description:

This package provides a unified method, called M statistic, is provided for detecting phylogenetic signals in continuous traits, discrete traits, and multi-trait combinations. Blomberg and Garland (2002) <doi:10.1046/j.1420-9101.2002.00472.x> provided a widely accepted statistical definition of the phylogenetic signal, which is the "tendency for related species to resemble each other more than they resemble species drawn at random from the tree". The M statistic strictly adheres to the definition of phylogenetic signal, formulating an index and developing a method of testing in strict accordance with the definition, instead of relying on correlation analysis or evolutionary models. The novel method equivalently expressed the textual definition of the phylogenetic signal as an inequality equation of the phylogenetic and trait distances and constructed the M statistic. The M statistic implemented in this package is based on the methodology described in Yao and Yuan (2025) <doi:10.1002/ece3.71106>. If you use this method in your research, please cite the paper.

r-publicationbiasbenchmark 0.1.3
Propagated dependencies: r-sandwich@3.1-1 r-rdpack@2.6.4 r-pwr@1.3-0 r-puniform@0.2.8 r-osfr@0.2.9 r-numderiv@2016.8-1.1 r-metafor@4.8-0 r-mass@7.3-65 r-lmtest@0.9-40 r-clubsandwich@0.6.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://github.com/FBartos/PublicationBiasBenchmark
Licenses: GPL 3
Build system: r
Synopsis: Benchmark for Publication Bias Correction Methods
Description:

This package implements a unified interface for benchmarking meta-analytic publication bias correction methods through simulation studies (see Bartoš et al., 2025, <doi:10.48550/arXiv.2510.19489>). It provides 1) predefined data-generating mechanisms from the literature, 2) functions for running meta-analytic methods on simulated data, 3) pre-simulated datasets and pre-computed results for reproducible benchmarks, 4) tools for visualizing and comparing method performance.

r-proteinpca 0.1.1
Propagated dependencies: r-gridextra@2.3 r-ggplot2@4.0.1
Channel: guix-cran
Location: guix-cran/packages/p.scm (guix-cran packages p)
Home page: https://cran.r-project.org/package=ProteinPCA
Licenses: GPL 3
Build system: r
Synopsis: Principal Component Analysis (PCA) Tool on Protein Expression Data
Description:

Analysis of protein expression data can be done through Principal Component Analysis (PCA), and this R package is designed to streamline the analysis. This package enables users to perform PCA and it generates biplot and scree plot for advanced graphical visualization. Optionally, it supports grouping/clustering visualization with PCA loadings and confidence ellipses. With this R package, researchers can quickly explore complex protein datasets, interpret variance contributions, and visualize sample clustering through intuitive biplots. For more details, see Jolliffe (2001) <doi:10.1007/b98835>, Gabriel (1971) <doi:10.1093/biomet/58.3.453>, Zhang et al. (2024) <doi:10.1038/s41467-024-53239-9>, and Anandan et al. (2022) <doi:10.1038/s41598-022-07781-5>.

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